Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…In contrast, nuclear magnetic resonance (NMR) measurements, which provide information on pore body size distribution, are faster and can be leveraged to estimate capillary pressure using machine learning algorithms. Recently, artificial intelligence methods have also been applied to capillary pressure prediction (Qi et al., 2024).Currently, no readily applicable predictive model exists for estimating an entire capillary pressure curve directly from standard petrophysical logs and core data. …”
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Early Detection of Soil Salinization by Means of Spaceborne Hyperspectral Imagery by Giacomo Lazzeri, Robert Milewski, Saskia Foerster, Sandro Moretti, Sabine Chabrillat

“…Both datasets were pre-processed with multiple data transformation algorithms and 2D correlograms, PLSR and the Random Forest regressor were tested to identify the best model for salinity detection. …”
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Construction and analysis of a prognostic risk scoring model for gastric cancer anoikis-related genes based on LASSO regression by Ai CHEN, Xiaowei CHEN, Yanan WANG, Xiaobing SHEN

“…Gene expression levels in gastric cancer clinical samples and cells were detected by real-time quantitative PCR (RT-qPCR); Kaplan-Meier (KM) survival curves, univariate and multivariate Cox regression analyses were used to verify the predictive efficiency of the prognostic risk scoring model for the prognosis of gastric cancer patients; CIBERSORT and ESTIMATE algorithms were used to analyze the immune cell infiltration levels in patients with different risk groups; the correlation between risk scores and immune checkpoint expression levels in gastric cancer patients was analyzed using the R package "ggplot2" and "ggExtra", and the correlation between tumor mutation burden (TMB) and risk scores was assessed; chemotherapy drug sensitivity analysis was used to evaluate the value of the constructed prognostic risk scoring model in gastric cancer chemotherapy. …”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…Finally, machine learning models were developed using these variables to predict sarcopenia and CD. <b>Results</b>: Models based on sensor data, CV data, and a combination of both technologies achieved high predictive accuracy, particularly for CD. …”
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Pharmacological potential of 3,5-dimethyl-4-(3-(5-nitrofuran-2-yl)allylidenamino)-1-alkyl-1,2,4-triazolium bromides by A. S. Hotsulia, O. I. Panasenko, T. S. Brytanova

“…A molecular docking method that uses a variety of computational algorithms to predict and analyze interactions, including determining the presence of possible binding sites, estimating binding energies, and the spatial arrangement of molecules. …”
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Assessment of prognosis and responsiveness to immunotherapy in colorectal cancer patients based on the level of immune cell infiltration by Kaili Liao, Minqi Zhu, Lei Guo, Zijun Gao, Jinting Cheng, Bing Sun, Yihui Qian, Bingying Lin, Jingyan Zhang, Tingyi Qian, Yixin Jiang, Yanmei Xu, Qionghui Zhong, Xiaozhong Wang

“…Furthermore, an accurate prognostic risk prediction model based on the co-expression of relevant genes by immune cells was developed, enabling precise prediction of survival of colon cancer patients. …”
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The role and prognostic value of PANoptosis-related genes in skin cutaneous melanoma by Huijing Feng, Linzi Jia, Yanan Ma, Pengmin Liu, Xiaoling Yang, Lina Hu, Kai Xu, Fan Yang, Dongfeng Zhang, Jian Li, Qi Mei, Fei Han

“…Prognostic genes for SKCM were derived using Cox analysis and machine learning algorithms, leading to the construction and validation of a prognostic model. …”
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Comprehensive analysis of phagocytosis regulatory genes in bladder cancer: implications for prognosis and immunotherapy by Xueming Ma, Xueming Ma, Xueming Ma, Dongnuan Yao, Dongnuan Yao, Dongnuan Yao, Weitao Yu, Weitao Yu, Weitao Yu, Gongping Wu, Gongping Wu, Gongping Wu, Chengwei Fan, Chengwei Fan, Chengwei Fan, Junqiang Tian, Junqiang Tian, Junqiang Tian

“…The constructed prognostic model showed excellent predictive performance, and the areas under the curves of survival rates at different times were all high in both the training set and the test set. …”
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Computer Viewing Model for Classification of Erythrocytes Infected with <i>Plasmodium</i> spp. Applied to Malaria Diagnosis Using Optical Microscope by Eduardo Rojas, Irene Cartas-Espinel, Priscila Álvarez, Matías Moris, Manuel Salazar, Rodrigo Boguen, Pablo Letelier, Lucia San Martín, Valeria San Martín, Camilo Morales, Neftalí Guzmán

“…<i>Conclusions:</i> Based on the results, we propose a convolutional neural network model (VGG-19) for malaria diagnosis that can be applied in low-complexity laboratories thanks to its ease of implementation and high predictive performance.…”
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Remote sensing inversion of nitrogen content in silage maize plants based on feature selection by Kejing Cheng, Kejing Cheng, Jixuan Yan, Jixuan Yan, Guang Li, Guang Li, Weiwei Ma, Weiwei Ma, Zichen Guo, Zichen Guo, Wenning Wang, Wenning Wang, Haolin Li, Qihong Da, Qihong Da, Xuchun Li, Xuchun Li, Yadong Yao, Yadong Yao

“…In studies on nitrogen content inversion in the maize canopy, the random forest (RF) algorithm, coupled with PLSR, demonstrated superior predictive performance. …”
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Using big data analytics to improve HIV medical care utilisation in South Carolina: A study protocol by Mohammad Rifat Haider, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Xiaoming Li

“…In addition, established secure data governance rules, data encryption and encrypted predictive techniques will be deployed. In addition to the data anonymisation as a part of privacy-preserving analytics, encryption schemes that protect running prediction algorithms on encrypted data will also be deployed. …”
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P85 | ALTERATION OF SUBMUCOSAL AND MYENTERIC GANGLIA IN SEVERE GUT DYSMOTILITY: A QUANTITATIVE MORPHOMETRIC ANALYSIS

“…This reduction remained consistent only in the AN and DEG subgroups. …”
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ANALYSIS OF GENERAL PLOW BODY TRACTIVE RESISTANCE by A. Yu. Izmaylov, A. A. Artyushin, N. E. Evtyushenkov, G. S. Bisenov, V. F. Rozhin, D. N. Kynev

“…Rational forms of the organization of operations enable reduction of standing time of combines, increase capacity of transportation vehicles and by that grain loss reduction owing to reduction reducing of harvest terms. …”
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Medical management after subthalamic stimulation in Parkinson’s disease: a phenotype perspective by Ana Paula BERTHOLO, Carina FRANÇA, Wilma Silva FIORINI, Egberto Reis Barbosa, Rubens Gisbert CURY

“…In a subset of patients with severe dyskinesia before surgery, an initial reduction in levodopa seems to be a more reasonable approach. …”
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Spatial Quality Control Method for Surface Temperature Observations Based on Multiple Elements by Xiaoling Ye, Xing Yang, Xiong Xiong, Shuai Yang, Yang Chen

“…However, machine learning algorithms are slower than traditional mathematical models. …”
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Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement. by José L Safanelli, Tomislav Hengl, Leandro L Parente, Robert Minarik, Dellena E Bloom, Katherine Todd-Brown, Asa Gholizadeh, Wanderson de Sousa Mendes, Jonathan Sanderman

“…From independent model evaluation, we found that Cubist comes out as the best-performing ML algorithm for the calibration and delivery of reliable outputs (prediction uncertainty and representation flag). …”
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Key Technologies in Intelligent O&M System Construction for Urban Rail Transit Communication by WANG Xianlei

“…The multi-source heterogeneous data fusion and analysis technologies are applied to communication system fault diagnosis and prediction. An equipment health index algorithm model and a big data architecture are proposed, and a tracking and evaluation platform encompassing ′cloud-data-intelligence′ is built. …”
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Application of Neural Network Models for Analyzing the Impact of Flight Speed and Angle of Attack on Flow Parameter Non-Uniformity in a Turbofan Engine Inlet Duct by Adam Kozakiewicz, Maciej Adamczyk, Rafał Kieszek

“…The ANN was trained using the CFG algorithm, and the predictive accuracy was assessed through the determination coefficients computed by comparing ANN-based estimates with numerical simulation results. …”
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Development of a mathematical model of dependence of specific volumetric electrical resistance of SIW-4 insulation on factors affecting its reliability by Denisov I. V.

“…It also opens up the possibility of developing the second stage of the study, associated with the construction of an algorithm for the method of predictive assessment of the residual life of the insulation material of the conductor under study.…”
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Cancer Patients Missing Pain Score Information:- Application with Imputation Techniques by Gajendra Vishwakarma, Atanu Bhattacharjee, Jesna Jose, Ramesh V

“…Interpretation and Conclusion: The EM algorithm shows the least percentage change from observed values in both visits followed by predictive mean matching method and MCMC methods. …”
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